Analysis of ecological effects of comprehensive treatment in the Tarim River Basin using remote sensing data

Based on multi-type,multi-temporal remote sensing data,we have monitored recent changes in cultivated land use and vegetation,in sandy areas and salinized desertification in the Green Corridor zone of the main channel of the Tarim River Basin.The results of our investigation show that the ecological environment in the Green Corridor of the main channel of the Tarim River Basin has conspicuously improved from 2002 to 2004.These improvements show up largely in such aspects as an increase in the rate of vegetation cover,a reduction in desertification land areas and a weakening in the intensity of sandy and the salinized land.On the other hand,the cultivated area in the Tarim River Basin significantly increased from 2002 to 2004.The rate of growth in cultivated areas during this period was significantly higher than that from 1999 to 2002.The increase in the use of irrigation resulting from the substantial increase in cultivated areas has a long-term potential restraining effect on the restoration of ecological functions of the Tarim River.

Remote Monitoring of Expansion of Aquaculture Ponds Along Coastal Region of the Yellow River Delta from 1983 to 2015

Aquaculture ponds are one of the fastest-growing land use types in valuable and fertile coastal areas and have caused serious environmental problems. Quantitative assessment of the extent, spatial distribution, and dynamics of aquaculture ponds is of utmost importance for sustainable economic development and scientific management of land and water resources in the coastal area. An object-oriented classification approach was applied to Landsat images acquired over three decades to investigate the long-term change of aquaculture ponds in the coastal region of the Yellow River Delta. The results indicated that the aquaculture ponds in the study area undergone a sharp expansion from 40.38 km^2 in 1983 to 1406.89 km^2 in 2015, and the fast expansion occurred during the period of 2010–2015 and 1990–2000. Natural wetlands, especially mudflat, and cropland were main land use types contributing to the increase of aquaculture ponds. The patches of aquaculture ponds were consequently prevalence in the north of the Yellow River Estuary and landscape metrics indicated an increase of the aquaculture ponds of the study area in the quantity and complexity. The expansion of aquaculture ponds inevitably had negative effects on the coastal environment, including loss of natural wetlands, water pollution and land subsidence, etc. The results from this study provide baseline data and valuable information for efficiently planning and managing aquaculture practices and for effectively implementing adequate regulations and protection measures.

Changes in Huanghe (Yellow) River estuary since artificial re-routing in 1996

With the combination of historical data, field observations and satellite remotely sensed images (Landsat TM/ ETM+ and CBERS), changes in Huanghe (Yellow) River estuary since 1996 when artificial Chahe distributary was built up were studied, mainly including water and sediment discharge from the river, tides, tidal currents, suspended sediment diffusion, coastline changes and seabed development. During following six and half years (up to the end of 2002), runoff and sediment loads into the river mouth declined dramatically. At the beginning of the re-routing, abundant sediment loads from the river filled up nearshore shallow water areas so that the newborn delta prograded quickly. With rapid decrease of sediment loads transported to the estuary, the delta retrograded. In 1997, subaerial tip of the abandoned delta receded 1.5km; its annual mean recession rate was about 150 m in following years. In addition, marine dynamic condition near the artificial outlet had also changed. Under the interaction of ocean and river flow, most of incoming sediment loads deposited in the vicin- ity of the outlet. Seabed erosion occurred at the subaqueous delta front. Between 1999 and 2002, erosion thick- ness averaged at 0.3 m in the subaqueous delta of 585.5 km2.

Monitoring of winter wheat distribution and phenological phases based on MODIS time-series： A case study in the Yellow River Delta, China

Accurate winter wheat identification and phenology extraction are essential for field management and agricultural policy making. Here, we present mechanisms of winter wheat discrimination and phenological detection in the Yellow River Delta（YRD） region using moderate resolution imaging spectroradiometer（MODIS） time-series data. The normalized difference vegetation index（NDVI） was obtained by calculating the surface reflectance in red and infrared. We used the Savitzky-Golay filter to smooth time series NDVI curves. We adopted a two-step classification to identify winter wheat. The first step was designed to mask out non-vegetation classes, and the second step aimed to identify winter wheat from other vegetation based on its phenological features. We used the double Gaussian model and the maximum curvature method to extract phenology. Due to the characteristics of the time-series profiles for winter wheat, a double Gaussian function method was selected to fit the temporal profile. A maximum curvature method was performed to extract phenological phases. Phenological phases such as the green-up, heading and harvesting phases were detected when the NDVI curvature exhibited local maximum values. The extracted phenological dates then were validated with records of the ground observations. The spatial patterns of phenological phases were investigated. This study concluded that, for winter wheat, the accuracy of classification is 87.07%, and the accuracy of planting acreage is 90.09%. The phenological result was comparable to the ground observation at the municipal level. The average green-up date for the whole region occurred on March 5, the average heading date occurred on May 9, and the average harvesting date occurred on June 5. The spatial distribution of the phenology for winter wheat showed a significant gradual delay from the southwest to the northeast. This study demonstrates the effectiveness of our proposed method for winter wheat classification and phenology detection.

Estimation model of winter wheat disease based on meteorological factors and spectral information

Wheat scab(WS,Fusarium head blight),one of the most severe diseases of winter wheat in Yangtze-Huaihe river region,whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and achieve the purpose of reducing yield loss.In the present study,remote sensing monitoring on WS was conducted in 4 counties in Yangtze-Huaihe river region.Sensitive factors of WS were selected to establish the remote sensing estimation model of winter wheat scab index(WSI)based on interactions between spectral information and meteorological factors.The results showed that:1)Correlations between the daily average temperature(DAT)and daily average relative humidity(DAH)at different time scales and WSI were significant.2)There were positive linear correlations between winter wheat biomass,leaf area index(LAI),leaf chlorophyll content(LCC)and WSI.3)NDVI(normalized difference vegetation index),RVI(ratio vegetation index)and DVI(difference vegetation index)which had a good correlation with LAI,biomass and LCC,respectively,and could be used to replace them in modeling.4)The estimated values of the model were consistent with the measured values(RMSE=5.3%,estimation accuracy=90.46%).Estimation results showed that the model could efficiently estimate WS in Yangtze-Huaihe river region.